The long term objective of this project is to solve the truncation problem in cone-beam tomography, and to implement and freely distribute image reconstruction software suitable for the most common cone-beam imaging configurations. The specific aims are: 1) to devise, implement, and make publicly available, fast accurate image reconstruction code for cone-beam computed tomography (CBCT) geometries where the source and detector rotate once (or slightly more than once) about the patient, and the projections are always truncated axially (and may also be truncated transaxially), 2) to devise, implement, and make publicly available, fast accurate image reconstruction code for CBCT geometries tailored to C-arm based CT with projections measured over an angular range of about 180 degrees, and with relevant patterns of truncation, and 3) to design and implement simple practical calibration methods from which geometric reconstruction parameters are automatically obtained and passed to the reconstruction algorithms for the scanner configurations of aims 1 and 2. The methods involve devising algorithms that are impervious to the propagation of false information that is normally concomitant with truncated projection data. Six cone-beam configurations will be considered, and algorithms will be devised by assembling fundamental mathematical tools which have been successful in solving certain specific cone-beam truncation problems in the past. The algorithms will be tested with computer simulated data and phantom measurements from benchtop and physical scanners. Automated calibration will be devised by extending existing analytic approaches, and tested against chi-squared approaches using simulated and real data. The health benefits of this project relate to the transition of cone-beam tomography from its current status as primarily a high-contrast imaging tool to a fast, quantitative, volume imaging modality with widespread applications in image guidance and diagnosis.